75 lines
2.0 KiB
Python
Executable File
75 lines
2.0 KiB
Python
Executable File
#!/usr/bin/env python3
|
|
|
|
import json
|
|
from typing import Dict
|
|
|
|
import onnx
|
|
from onnxruntime.quantization import QuantType, quantize_dynamic
|
|
|
|
|
|
def add_meta_data(filename: str, meta_data: Dict[str, str]):
|
|
"""Add meta data to an ONNX model. It is changed in-place.
|
|
|
|
Args:
|
|
filename:
|
|
Filename of the ONNX model to be changed.
|
|
meta_data:
|
|
Key-value pairs.
|
|
"""
|
|
model = onnx.load(filename)
|
|
|
|
while len(model.metadata_props):
|
|
model.metadata_props.pop()
|
|
|
|
for key, value in meta_data.items():
|
|
meta = model.metadata_props.add()
|
|
meta.key = key
|
|
meta.value = value
|
|
|
|
onnx.save(model, filename)
|
|
|
|
|
|
def main():
|
|
with open("./vocab.json", "r", encoding="utf-8") as f:
|
|
tokens = json.load(f)
|
|
|
|
vocab_size = len(tokens)
|
|
with open("tokens.txt", "w", encoding="utf-8") as f:
|
|
for token, idx in tokens.items():
|
|
if idx == 0:
|
|
f.write("<blk> 0\n")
|
|
else:
|
|
f.write(f"{token} {idx}\n")
|
|
|
|
filename = "model.onnx"
|
|
meta_data = {
|
|
"model_type": "telespeech_ctc",
|
|
"version": "1",
|
|
"model_author": "Tele-AI",
|
|
"comment": "See also https://github.com/lovemefan/telespeech-asr-python",
|
|
"license": "https://github.com/Tele-AI/TeleSpeech-ASR/blob/master/TeleSpeech%E6%A8%A1%E5%9E%8B%E7%A4%BE%E5%8C%BA%E8%AE%B8%E5%8F%AF%E5%8D%8F%E8%AE%AE.pdf",
|
|
"url": "https://github.com/Tele-AI/TeleSpeech-ASR",
|
|
}
|
|
|
|
add_meta_data(filename, meta_data)
|
|
|
|
filename_int8 = f"model.int8.onnx"
|
|
quantize_dynamic(
|
|
model_input=filename,
|
|
model_output=filename_int8,
|
|
op_types_to_quantize=["MatMul"],
|
|
weight_type=QuantType.QInt8,
|
|
)
|
|
|
|
# filename_uint8 = f"model.uint8.onnx"
|
|
# quantize_dynamic(
|
|
# model_input=filename,
|
|
# model_output=filename_uint8,
|
|
# op_types_to_quantize=["MatMul"],
|
|
# weight_type=QuantType.QUInt8,
|
|
# )
|
|
|
|
|
|
if __name__ == "__main__":
|
|
main()
|